Silent cascade Enhancing location privacy without communication QoS degradation.pdf

Silent Cascade: Enhancing Location Privacy without Communication QoS Degradation Leping Huang1,2, Hiroshi Yamane2, Kanta Matsuura2, and Kaoru Sezaki2 1 Nokia Research Center Japan,1-8-1,Shimomeguro, Meguro-ku, Tokyo, Japan 2 University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, Japan Abstract. In a wireless communication network, it is possible to locate a user and track its trajectory based on its transmission, during commu- nication with access points. This type of tracking leads to the breach of a user’s location privacy. Prior solutions to this problem enhances user’s lo- cation privacy at the expense of communication Quality of Service(QoS) degradation. In this paper, we propose silent cascade to enhance a user’ location privacy by trading users’ delay in silent cascade for anonymity. As a result, it avoids the problem of QoS degradation in prior solutions. Furthermore, we abstract silent cascade as a mix-network based formal model, and use this model to evaluate the performance of silent cascade. Study results prove the effectiveness of silent cascade under different types of QoS requirements. Besides, we also derive the optimal config- uration of silent cascade to achieves target anonymity within minimum duration of time. and the theoretical upper bound of a silent cascade’s anonymity. 1 Introduction Recent technological advances in wireless location-tracking present unprece- dented opportunities for monitoring the movements of individuals. While such technology can support many useful location-based services (LBSs), which tailor their functionality to a user’s current location, privacy concerns might seriously hamper user acceptance. Some of those systems can accurately track users’ po- sition by overhearing other nodes’ frames. We believe that those systems may cause serious location privacy problem on normal users of wireless communica- tion. In this paper, we concentrate on location privacy in the context of trajectory privacy. Trajectory privacy represent